Due to the advance in imaging devices, more and more videos (sequences of images, also known as, motion pictures) are being generated anytime and anywhere. Moreover, in the pursuit of higher resolution, the video size keeps increasing. These all involve a large amount of data to be handled. This poses a huge challenge in processes such as displaying, transmitting and storing the videos. Therefore, there is a need for video coding techniques so that video can be compressed without any loss to its quality.
Regarding the quality, less distortion is desired and the distortion is traditionally measured by quantitative metrics such as mean square error (MSE) and peak signal-to-noise ratio (PSNR). However, these quantitative metrics may not reflect how a human observer perceives an image and how severe the distortion is in the eyes of the human observer. Therefore, there is a need to further increase the compression ratio without introducing additional visual distortion by taking the properties of how humans perceive things visually into consideration. In other words, a subjective test of how humans perceive an image is important. Therefore, there is a need to maintain a user's visual perception while performing video processing more efficiently.
Furthermore, pursuant to the development of video standards, an increasing number of features are incorporated in current and future video standards. One of these features is to allow various block sizes in video coding processes, for example, adaptive block-size transform (ABT). This helps to improve image quality by considering the image contents. Therefore, there is a need to enable ABT in video coding, for example, in compliance with video standards such as H.264/AVC.